Keyword matches words; semantic matches meaning and exact titles or names; hybrid combines both. In keyword mode, use quotation marks for exact phrases. Author matches published credits. Year applies to posts; wiki entries have no author or publication year. You can also use author:"Ada" or type:podcast in non-regex searches.
author:"Ada"
type:podcast
Explore articles, conversations, and the wiki.
Articles, conversations, profiles, and grounded writeups.
Select Apply filters to update results.
Search or filters have changed. The results below still show the previous search; select Search or Apply filters to update them.
128 results in retrieved candidates · Filters applied
Dyna-2: General Purpose Physical Agents with Hour-Long Autonomy — Jason Ma, Dyna Robotics Our first robotics pod with Dyna’s Chief Scientist on their big bet on World Action Models & the Next Frontier of Physical AI Our first robotics pod…
Retrieval After RAG: Hybrid Search, Agents, and Database Design — Simon Hørup Eskildsen of Turbopuffer Latent.Space
…here:— (@)From the rapid rise of Claude Code to a future where agents can rewrite their own harnesses, collaborate across teams, and operate across cloud and local environments, the way we build software is changing extraordinarily fast. In…
…feature was Shunyu Yao, who happened to focus on Language Agents for his thesis and immediately went to work on them for OpenAI. Our pick this year is Jack Morris, who bucks the “hot” trends by -not- working on agents, benchmarks, or VS…
…we explore the evolution of fine-tuning in the age of AI agents and the critical shift from supervised fine-tuning to reinforcement learning. Kyle shares his journey from leading YC’s Startup School to building OpenPipe, initially focused…
…curtains to talk about finally shipping the Knowledge Work AI agents the world has been waiting for. Latent.Space
Dreamer: the Personal Agent OS — David Singleton /dev/agents is out of stealth as Dreamer, and the vision is staggeringly ambitious. Latent.Space
The Agent Network — Dharmesh Shah Dharmesh Shah on Intelligent Agents, Market Inefficiencies, and Building the Next AI Marketplace Latent.Space
…AI infrastructure company. It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation…
…how SOP-driven agents beat overengineered RL in ops, why Brex lets employees “build their own AI stack” instead of picking winners [https://www.conductorone.com/customers/brex/], and how a small, founder-heavy AI team is shipping production…
…and prompt optimizers aren’t a promising direction for coding agents. Amp Code: https://ampcode.com/ Latent Space: https://latent.space/ Full Video EpisodeTimestamps00:00 Introduction00:41 Transition from Cody to Amp03:18 The Importance of …
…and the emerging Code x LLM paradigms. Plus: Recursive Function Agents! Latent.Space
Sign in with Google, or get the newsletter by email.
Loading Google sign-in…
Free. Change your preferences or unsubscribe any time.
Uncheck all to create an account without newsletter emails.
Discover technical newsletters we recommend, then explore Latent Space membership. Both are optional.
Your newsletter choice is optional. How we use your account data.
Please enable JavaScript to sign in or subscribe. You can still read the articles.
